Text-to-image diffusion models can generate diverse, high-fidelity images based on user-provided text prompts. They operate by mapping a random sample from a…
Text-to-image diffusion models can generate diverse, high-fidelity images based on user-provided text prompts. They operate by mapping a random sample from a high-dimensional space, conditioned on a user-provided text prompt, through a series of denoising steps. This results in a representation of the corresponding image, . These models can also be used for more complex tasks such as image…